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Morphology, Phonology & FSTs

Morphology, Phonology & FSTs. Shallow Processing Techniques for NLP Ling570 October 12, 2011. Roadmap. Motivation: Representing words A little (mostly English) Morphology Stemming FSTs & Morphology Stemming Morphological analysis FSTs & Phonology. Words.

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Morphology, Phonology & FSTs

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  1. Morphology, Phonology & FSTs Shallow Processing Techniques for NLP Ling570 October 12, 2011

  2. Roadmap • Motivation: • Representing words • A little (mostly English) Morphology • Stemming • FSTs & Morphology • Stemming • Morphological analysis • FSTs & Phonology

  3. Words • Goal: Compact representation of all surface forms in a language

  4. Lexicon • Goal: Compact representation of all surface forms in a language • Enumeration: • Impractical for morphologically rich languages • Descriptively unsatisfying for most languages

  5. Lexicon • Goal: Compact representation of all surface forms in a language • Enumeration: • Impractical for morphologically rich languages • Descriptively unsatisfying for most languages • Orthographic variation: • Fly+er Flier

  6. Lexicon • Goal: Compact representation of all surface forms in a language • Enumeration: • Impractical for morphologically rich languages • Descriptively unsatisfying for most languages • Orthographic variation: • Fly+er Flier • Morphological variation: • saw + s  saws; fish + s  fish; goose + s  geese

  7. Lexicon • Goal: Compact representation of all surface forms in a language • Enumeration: • Impractical for morphologically rich languages • Descriptively unsatisfying for most languages • Orthographic variation: • Fly+er Flier • Morphological variation: • saw + s  saws; fish + s  fish; goose + s  geese • Phonological variation: • dog + s  dog + /z/; fox + s  fox + /IH Z/

  8. Morphological Parsing • Goal: Take a surface word form and generate a linguistic structure of component morphemes • A morpheme is the minimal meaning-bearing unit in a language. • Stem: the morpheme that forms the central meaning unit in a word • Affix: prefix, suffix, infix, circumfix • Prefix: e.g., possible impossible • Suffix: e.g., walk walking • Infix: e.g., hingihumingi (Tagalog) • Circumfix: e.g., sagengesagt (German)

  9. Combining Morphemes • Inflection: Stem + gram. morpheme  same class • E.g.: help + ed  helped

  10. Combining Morphemes • Inflection: Stem + gram. morpheme  same class • E.g.: help + ed  helped • Derivation: Stem + gram. morpheme  new class • E.g. Walk + er  walker (N)

  11. Combining Morphemes • Inflection: Stem + gram. morpheme  same class • E.g.: help + ed  helped • Derivation: Stem + gram. morpheme  new class • E.g. Walk + er  walker (N) • Compounding: multiple stems  new word • E.g. doghouse, catwalk, …

  12. Combining Morphemes • Inflection: Stem + gram. morpheme  same class • E.g.: help + ed  helped • Derivation: Stem + gram. morpheme  new class • E.g. Walk + er  walker (N) • Compounding: multiple stems  new word • E.g. doghouse, catwalk, … • Clitics: stem+clitic • I + ll  I’ll; he + is  he’s

  13. Inflectional Morphology(Mostly English) • Relatively simple inflectional system • Nouns, verbs, some adjectives

  14. Inflectional Morphology(Mostly English) • Relatively simple inflectional system • Nouns, verbs, some adjectives • Noun inflection: • Only plural, possessive • Non-English???

  15. Inflectional Morphology(Mostly English) • Relatively simple inflectional system • Nouns, verbs, some adjectives • Noun inflection: • Only plural, possessive • Non-English??? • Plural: mostly stem + ‘s’, ‘es’ after s,z,sh,ch,x • Possessive:

  16. Inflectional Morphology(Mostly English) • Relatively simple inflectional system • Nouns, verbs, some adjectives • Noun inflection: • Only plural, possessive • Non-English??? • Plural: mostly stem + ‘s’, ‘es’ after s,z,sh,ch,x • Possessive: sg, irregpl: +’s; regpl, after s,z: ‘

  17. Verb Inflectional Morphology • Classes: • Main (eat, hit), modal (can, should), primary (be, have) • Only main, primary inflected

  18. Verb Inflectional Morphology • Classes: • Main (eat, hit), modal (can, should), primary (be, have) • Only main, primary inflected • Regular verbs: Forms predictable from stem, productive

  19. Verb Inflectional Morphology • Classes: • Main (eat, hit), modal (can, should), primary (be, have) • Only main, primary inflected • Regular verbs: Forms predictable from stem, productive • Irregular verbs: Only about 250, but very frequent

  20. Derivational Morphology • Relatively complex, common in English • Nominalization: Verb or Adj + affix  Noun

  21. Derivational Morphology • Relatively complex, common in English • Nominalization: Verb or Adj + affix  Noun • Adjectives: Verb or Noun + affix  Adj

  22. Derivational Morphology • Relatively complex, common in English • Nominalization: Verb or Adj + affix  Noun • Adjectives: Verb or Noun + affix  Adj

  23. Cliticization • Clitics: between affix and word • Affix: short, reduced • Word: act as pronouns, articles, conj, verbs

  24. Cliticization • Clitics: between affix and word • Affix: short, reduced • Word: act as pronouns, articles, conj, verbs • In English: • Presence is (mostly) unambiguous: ‘ • Meaning is often ambiguous: e.g. he’s

  25. Cliticization • Clitics: between affix and word • Affix: short, reduced • Word: act as pronouns, articles, conj, verbs • In English: • Presence is (mostly) unambiguous: ‘ • Meaning is often ambiguous: e.g. he’s • More complex in other languages: e.g. Arabic

  26. Cliticization • Clitics: between affix and word • Affix: short, reduced • Word: act as pronouns, articles, conj, verbs • In English: • Presence is (mostly) unambiguous: ‘ • Meaning is often ambiguous: e.g. he’s • More complex in other languages: e.g. Arabic • Can prefix (proclitic) article, prep, conj, • No markers • Removal of such clitics often referred to as light stemming

  27. Stemming • Simple type of morphological analysis • Commonly used in information retrieval (IR) • Supports matching using base form • e.g. Television, televised, televising  televise

  28. Stemming • Simple type of morphological analysis • Commonly used in information retrieval (IR) • Supports matching using base form • e.g. Television, televised, televising  televise • Typically improves retrieval of short documents – why?

  29. Stemming • Simple type of morphological analysis • Commonly used in information retrieval (IR) • Supports matching using base form • e.g. Television, televised, televising  televise • Typically improves retrieval of short documents – why? • Most popular: Porter stemmer (snowball.tartarus.org)

  30. Stemming • Simple type of morphological analysis • Commonly used in information retrieval (IR) • Supports matching using base form • e.g. Television, televised, televising  televise • Typically improves retrieval of short documents – why? • Most popular: Porter stemmer (snowball.tartarus.org) • Task: Given surface form, produce base form • Typically, removes suffixes

  31. Stemming • Simple type of morphological analysis • Commonly used in information retrieval (IR) • Supports matching using base form • e.g. Television, televised, televising  televise • Typically improves retrieval of short documents – why? • Most popular: Porter stemmer (snowball.tartarus.org) • Task: Given surface form, produce base form • Typically, removes suffixes • Model: • Rule cascade • No lexicon!

  32. Porter Stemmer • Rule cascade: • Rule form: • (condition) PATT1  PATT2

  33. Porter Stemmer • Rule cascade: • Rule form: • (condition) PATT1  PATT2 • E.g. stem contains vowel, ING -> ε

  34. Porter Stemmer • Rule cascade: • Rule form: • (condition) PATT1  PATT2 • E.g. stem contains vowel, ING -> ε • ATIONAL  ATE

  35. Porter Stemmer • Rule cascade: • Rule form: • (condition) PATT1  PATT2 • E.g. stem contains vowel, ING -> ε • ATIONAL  ATE • Rule partial order: • Step1a: -s • Step1b: -ed, -ing

  36. Porter Stemmer • Rule cascade: • Rule form: • (condition) PATT1  PATT2 • E.g. stem contains vowel, ING -> ε • ATIONAL  ATE • Rule partial order: • Step1a: -s • Step1b: -ed, -ing • Step 2-4: derivational suffixes

  37. Porter Stemmer • Rule cascade: • Rule form: • (condition) PATT1  PATT2 • E.g. stem contains vowel, ING -> ε • ATIONAL  ATE • Rule partial order: • Step1a: -s • Step1b: -ed, -ing • Step 2-4: derivational suffixes • Step 5: cleanup • Pros:

  38. Porter Stemmer • Rule cascade: • Rule form: • (condition) PATT1  PATT2 • E.g. stem contains vowel, ING -> ε • ATIONAL  ATE • Rule partial order: • Step1a: -s • Step1b: -ed, -ing • Step 2-4: derivational suffixes • Step 5: cleanup • Pros: Simple, fast, buildable for a variety of languages • Cons:

  39. Porter Stemmer • Rule cascade: • Rule form: • (condition) PATT1  PATT2 • E.g. stem contains vowel, ING -> ε • ATIONAL  ATE • Rule partial order: • Step1a: -s • Step1b: -ed, -ing • Step 2-4: derivational suffixes • Step 5: cleanup • Pros: Simple, fast, buildable for a variety of languages • Cons: Overaggressive and underaggressive • Limited in application

  40. FST Morphological Analysis • Focus on English morphology • FSA acceptor: • cats  yes; foxes  yes; childs  no

  41. FST Morphological Analysis • Focus on English morphology • FSA acceptor: • cats  yes; foxes  yes; childs  no • FST morphological analyzer: • fox + N + pl  fox^s#

  42. FST Morphological Analysis • Focus on English morphology • FSA acceptor: • cats  yes; foxes  yes; childs  no • FST morphological analyzer: • fox + N + pl  fox^s# • FST for orthographic rules: • fox^s#  foxes#

  43. Morphological AnalysisComponents • Lexicon: List of stems and affixes • E.g.: cat: N • -s: Pl

  44. Morphological AnalysisComponents • Lexicon: List of stems and affixes • E.g.: cat: N • -s: Pl • Morphotactics: Model of morpheme ordering • Association with classes, affix ordering • E.g. Pl follows N

  45. Morphological AnalysisComponents • Lexicon: List of stems and affixes • E.g.: cat: N • -s: Pl • Morphotactics: Model of morpheme ordering • Association with classes, affix ordering • E.g. Pl follows N • Orthographic rules: Spelling rules • Changes when morphemes combine • E.g. y  ie in try + s

  46. Example • Goal: foxes  fox + N + Pl

  47. Example • Goal: foxes  fox + N + Pl • Surface: foxes

  48. Example • Goal: foxes  fox + N + Pl • Surface: foxes • Orthographic rules • Intermediate: fox s

  49. Example • Goal: foxes  fox + N + Pl • Surface: foxes • Orthographic rules • Intermediate: fox s • Lexicon + morphotactics • Lexical: fox + N + Pl

  50. Multiple Levels • Generation and Analysis • Generation: fox + N + Pl  fox^s#; fox^s#  foxes# • Analysis: foxes#  fox^s#; fox^s#  fox + N + Pl

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